I am making my way through the book “Analyzing Baseball Data with R.” I am recording my progress by posting my notes to Rpubs. I am recreating most of the examples in the book and doing most of the exercises that are prescribed at the end of each chapter. This post is about Chapter 4. I have skipped straight to Chapter 4 for the sake of these posts, because the first 3 chapters are not great content. Fairly boring.

Chapter 4 looks at the relationship between run differential and wins. It’s a straight forward relationship. If you score more than you allow, you ought to win more. It’s almost the the definition of winning. So that relationship is explored and a linear regression is modeled. The chapter then goes on to explore the Pythagorean Formula. The Pythagorean was developed by Bill James the father of Sabermetrics. The Pythagorean is compared to the linear regression taken previously. Then the Pythagorean is optimized using calculus and a linear regression.

It’s an interesting chapter here are my notes: